When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

The article introduces StockAgent, a multi-agent AI system utilizing large language models (LLMs) to simulate stock trading behaviors in response to external factors such as macroeconomic conditions and policy changes. StockAgent addresses the issue of test set leakage common in previous AI trading simulations, allowing for a more accurate analysis of trading behaviors and profitability under realistic market conditions. This framework provides insights that can enhance LLM-based investment strategies and stock recommendations, making it significant for practitioners in finance and AI.